Table Design

Stat 365: Statistical Communication

Wednesday, April 19th1

Today we will…

  • The role of tables
  • Table design
  • Practice with tables

The role of tables

Use a table when…1

  • The display will be used to look up individual values
  • The display will be used to compare individual values rather than a series or trend
  • Precise values are required
  • Values involve more than one unit of measure
  • Values must be presented at various levels of aggregation

Table Anatomy1

Table Tips

  • Tables should be self-sufficient and stand-alone. The reader should be able to understand the table without reading your discussion. Use titles, row headings, and column headings to convey:
    • Purpose
    • Context
    • Variables (units of measurement/categories)
    • Data sources (in footnotes)
    • Definitions of technical terms
  • Let the data speak for themselves – Simplicity!
  • Organize material in a meaningful way
  • Tables should never flow across a page break

Table Example: Mandela

Table X. Descriptive Statistics on Sample
Group Mean SD
Prompt 1 70.36364 18.54607
Prompt 2 87.96000 14.23165
  • Short, cryptic acronyms
  • References to prompt numbers not available to your reader
  • Excessive digits
Table X. Means and Standard Deviations of the Guesses for Mandela's Age of Death for each Numerical Anchoring of Participants to a Younger or Older Age
Numerical Anchor Mean (Years) Standard Deviation N
12 Years 70.4 18.5 22
120 Years 88.0 14.2 25
Note:
Data was collected from the Spring 2023 Stat 365 class at Cal Poly.
  • Labels clearly identify the concepts in each row
  • The variable can be defined in the data and methods section or a note to the table
  • For a non-scientific article, replace technical labels with everyday synonyms

Table Design

Align numbers to the right

Select your font to be legible

Variations in tables

Unidirectional categorical items are laid out in one direction only (think long data)

Bidirectional categorical items are laid out in both directions (think wide data)

Highlight what’s important!


Boldfaced or Italic text

Size

Color
intensity
Position

Common Errors1

  • Tables that are too large or too simple
  • Inclusion of nonessential data
  • Failure to use shading and bordering in tables
  • Redundancy with text
  • Excessive precision
  • Not self-explanatory
  • Design elements interfere with the clarity
  • Inadequate definition of symbols or abbreviations

Packages for tables in R

  • library(gt)
  • library(DT)
  • library(kable)
  • library(kableExtra)

Practice in table design

Can you sketch out a table of summary statistics for your data?

To do

Collect Data

  • Aim to have your data collected by, Monday 4/24
  • As soon as you have your data collected, start working on your analysis using statistical methods learned in previous courses.
  • REPRODUCIBILITY! Document EVERYTHING!
  • Read CwD 3.4: Tracking the Analysis

One-number Story

  • Draft: due Thursday, 4/20 at 11:59pm
  • Peer Review: due Sunday, 4/23 at 11:59pm
  • Final submission: due Thursday, 4/27 at 11:59pm

Listen to Storytelling with Data Podcasts (Data Viz) for next week

Read Communicating Data with Tableau for next week